Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-5593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Jul 2022
Model description paper |
| 21 Jul 2022
| 21 Jul 2022
SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level
Julien Ruffault
INRAE, URFM, 84000 Avignon, France
François Pimont
INRAE, URFM, 84000 Avignon, France
Hervé Cochard
Université Clermont Auvergne, INRAE, PIAF, 63000
Clermont-Ferrand, France
Jean-Luc Dupuy
INRAE, URFM, 84000 Avignon, France
Nicolas Martin-StPaul
CORRESPONDING AUTHOR
INRAE, URFM, 84000 Avignon, France
Related authors
Julien Ruffault, Thomas Curt, Nicolas K. Martin-StPaul, Vincent Moron, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 18, 847–856, https://doi.org/10.5194/nhess-18-847-2018, https://doi.org/10.5194/nhess-18-847-2018, 2018
Short summary
Short summary
Extreme wildfires events (EWE) have been recorded during the past year in the Mediterranean. By analyzing the climatic conditions associated with the French 2003 and 2016 fires seasons, we found that EWE were associated to two distinct climatic events whose frequencies are both expected to increase with global changes: hot droughts and long droughts. These results suggest that EWE are likely to become more common in the future and will certainly challenge fire management.
Arsène Druel, Julien Ruffault, Hendrik Davi, André Chanzy, Olivier Marloie, Miquel De Cáceres, Florent Mouillot, Christophe François, Kamel Soudani, and Nicolas K. Martin-StPaul
EGUsphere, https://doi.org/10.5194/egusphere-2024-1800, https://doi.org/10.5194/egusphere-2024-1800, 2024
Short summary
Short summary
Accurate radiation data are essential for understanding ecosystem growth. Traditional large-scale data lack the precision needed for complex terrains, e.g. mountainous regions. This study introduces a new model to enhance radiation data resolution using elevation maps, which accounts for sub-daily direct and diffuse radiation effects caused by terrain features. Tested on Mont Ventoux, this method significantly improves radiation estimates, benefiting forest growth and climate risk models.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Julien Ruffault, Thomas Curt, Nicolas K. Martin-StPaul, Vincent Moron, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 18, 847–856, https://doi.org/10.5194/nhess-18-847-2018, https://doi.org/10.5194/nhess-18-847-2018, 2018
Short summary
Short summary
Extreme wildfires events (EWE) have been recorded during the past year in the Mediterranean. By analyzing the climatic conditions associated with the French 2003 and 2016 fires seasons, we found that EWE were associated to two distinct climatic events whose frequencies are both expected to increase with global changes: hot droughts and long droughts. These results suggest that EWE are likely to become more common in the future and will certainly challenge fire management.
Related subject area
Biogeosciences
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Quantifying the role of ozone-caused damage to vegetation in the Earth system: A new parameterization scheme for photosynthetic and stomatal responses
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
DeepPhenoMem V1.0: Deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
Exploring the Potential of History Matching for Land Surface Model Calibration
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
Using Deep Learning to integrate paleoclimate and global biogeochemistry over Phanerozoic time
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Assimilation of Carbonyl Sulfide (COS) fluxes within the adjoint-based data assimilation system–Nanjing University Carbon Assimilation System (NUCAS v1.0)
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
Implementing a coral reef CaCO3 production module in the iLOVECLIM climate model
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-6, https://doi.org/10.5194/gmd-2024-6, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study introduces a new scheme to simulate surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal response to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2024-464, https://doi.org/10.5194/egusphere-2024-464, 2024
Short summary
Short summary
Our study employs Long Short-Term Memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlocking the secrets of vegetation phenology responses to climate change with deep learning techniques.
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2996, https://doi.org/10.5194/egusphere-2023-2996, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. Here we test a technique called “History matching” against more common approaches. This method adapts well to these models, helping better understand how they work and therefore how to make them more realistic.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Dongyu Zheng, Andrew Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-230, https://doi.org/10.5194/gmd-2023-230, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study uses a deep learning method to enhance the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model for more accurate predictions of climate shifts. The method may be critical in developing new fully-continuous methods that are able to translate over a moving continental surface in deep time with high-resolution at a reasonable computational expense.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-242, https://doi.org/10.5194/gmd-2023-242, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems as the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-238, https://doi.org/10.5194/gmd-2023-238, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through “data assimilation”, which blends numerical models and observations. Here, we present EAT, a flexible and efficient testbed that allows any scientist to explore and further develop the state-of-the-art in data assimilation.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
Short summary
Short summary
In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
EGUsphere, https://doi.org/10.5194/egusphere-2023-1162, https://doi.org/10.5194/egusphere-2023-1162, 2023
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon-climate model and its validation in comparison to existing modern data.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Cited articles
Abram, N. J., Henley, B. J., Sen Gupta, A., Lippmann, T. J. R., Clarke, H.,
Dowdy, A. J., Sharples, J. J., Nolan, R. H., Zhang, T., Wooster, M. J.,
Wurtzel, J. B., Meissner, K. J., Pitman, A. J., Ukkola, A. M., Murphy, B.
P., Tapper, N. J., and Boer, M. M.: Connections of climate change and
variability to large and extreme forest fires in southeast Australia,
Commun. Earth Environ., 2, 1–17, https://doi.org/10.1038/s43247-020-00065-8, 2021.
Adams, H. D., Zeppel, M. J. B., Anderegg, W. R. L., Hartmann, H.,
Landhäusser, S. M., Tissue, D. T., Huxman, T. E., Hudson, P. J., Franz,
T. E., Allen, C. D., Anderegg, L. D. L., Barron-Gafford, G. A., Beerling, D.
J., Breshears, D. D., Brodribb, T. J., Bugmann, H., Cobb, R. C., Collins, A.
D., Dickman, L. T., Duan, H., Ewers, B. E., Galiano, L., Galvez, D. A.,
Garcia-Forner, N., Gaylord, M. L., Germino, M. J., Gessler, A., Hacke, U.
G., Hakamada, R., Hector, A., Jenkins, M. W., Kane, J. M., Kolb, T. E., Law,
D. J., Lewis, J. D., Limousin, J.-M., Love, D. M., Macalady, A. K.,
Martínez-Vilalta, J., Mencuccini, M., Mitchell, P. J., Muss, J. D.,
O'Brien, M. J., O'Grady, A. P., Pangle, R. E., Pinkard, E. A., Piper, F. I.,
Plaut, J. A., Pockman, W. T., Quirk, J., Reinhardt, K., Ripullone, F., Ryan,
M. G., Sala, A., Sevanto, S., Sperry, J. S., Vargas, R., Vennetier, M., Way,
D. A., Xu, C., Yepez, E. A., and McDowell, N. G.: A multi-species synthesis
of physiological mechanisms in drought-induced tree mortality, Nat. Ecol.
Evol., 1, 1285–1291, https://doi.org/10.1038/s41559-017-0248-x, 2017.
Allen, C. D., Breshears, D. D., and McDowell, N. G.: On underestimation of
global vulnerability to tree mortality and forest die-off from hotter
drought in the Anthropocene, Ecosphere, 6, art129,
https://doi.org/10.1890/ES15-00203.1, 2015.
Arend, M., Link, R. M., Zahnd, C., Hoch, G., Schuldt, B., and Kahmen, A.:
Lack of hydraulic recovery as a cause of post-drought foliage reduction and
canopy decline in European beech, New Phytol., 234, 1195–1205,
https://doi.org/10.1111/nph.18065, 2022.
Bartlett, M. K., Scoffoni, C., and Sack, L.: The determinants of leaf turgor
loss point and prediction of drought tolerance of species and biomes: A
global meta-analysis, Ecol. Lett., 15, 393–405,
https://doi.org/10.1111/j.1461-0248.2012.01751.x, 2012.
Bartlett, M. K., Klein, T., Jansen, S., Choat, B., and Sack, L.: The
correlations and sequence of plant stomatal, hydraulic, and wilting
responses to drought, P. Natl. Acad. Sci. USA, 113, 13098–13103,
https://doi.org/10.1073/pnas.1604088113, 2016.
Billon, L. M., Blackman, C. J., Cochard, H., Badel, E., Hitmi, A.,
Cartailler, J., Souchal, R., and Torres-Ruiz, J. M.: The DroughtBox: A new
tool for phenotyping residual branch conductance and its temperature
dependence during drought, Plant Cell Environ., 43, 1584–1594,
https://doi.org/10.1111/pce.13750, 2020.
Brodribb, T. J., Powers, J., Cochard, H., and Choat, B.: Hanging by a
thread? Forests and drought, Science, 368, 261–266, https://doi.org/10.1126/science.aat7631, 2020.
Cheaib, A., Badeau, V., Boe, J., Chuine, I., Delire, C., Dufrêne, E.,
François, C., Gritti, E. S., Legay, M., Pagé, C., Thuiller, W.,
Viovy, N., and Leadley, P.: Climate change impacts on tree ranges: Model
intercomparison facilitates understanding and quantification of uncertainty,
Ecol. Lett., 15, 533–544, https://doi.org/10.1111/j.1461-0248.2012.01764.x,
2012.
Choat, B., Jansen, S., Brodribb, T. J., Cochard, H., Delzon, S., Bhaskar, R., Bucci, S. J., Feild, T.
S., Gleason, S. M., Hacke, U. G., Jacobsen, A. L., Lens, F., Maherali, H., Martínez-Vilalta, J.,
Mayr, S., Mencuccini, M., Mitchell, P. J., Nardini, A., Pittermann, J., Pratt, R. B., Sperry, J. S.,
Westoby, M., Wright, I. J., and Zanne, A. E.: Global convergence in the vulnerability of forests
to drought, Nature, 491, 4–8, https://doi.org/10.1038/nature11688, 2012.
Choat, B., Brodribb, T. J., Brodersen, C. R., Duursma, R. A., López, R., and Medlyn, B. E.:
Triggers of tree mortality under drought, Nature, 558, 531–539,
https://doi.org/10.1038/s41586-018-0240-x, 2018.
Christoffersen, B. O., Gloor, M., Fauset, S., Fyllas, N. M., Galbraith, D. R., Baker, T. R., Kruijt, B., Rowland, L., Fisher, R. A., Binks, O. J., Sevanto, S., Xu, C., Jansen, S., Choat, B., Mencuccini, M., McDowell, N. G., and Meir, P.: Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro), Geosci. Model Dev., 9, 4227–4255, https://doi.org/10.5194/gmd-9-4227-2016, 2016.
Chuine, I. and Cour, P.: Climatic determinants of budburst seasonality in
four temperate-zone tree species, New Phytol., 143, 339–349, 1999.
Cochard, H.: A new mechanism for tree mortality due to drought and
heatwaves, Peer Community J., 1, e36, https://doi.org/10.24072/PCJOURNAL.45,
2021.
Cochard, H., Pimont, F., Ruffault, J., and Martin-StPaul, N.: SurEau: a
mechanistic model of plant water relations under extreme drought, Ann. For.
Sci., 78, 1–23, https://doi.org/10.1007/s13595-021-01067-y, 2021.
Couvreur, V., Ledder, G., Manzoni, S., Way, D. A., Muller, E. B., and Russo,
S. E.: Water transport through tall trees: A vertically explicit, analytical
model of xylem hydraulic conductance in stems, Plant Cell Environ., 41,
1821–1839, https://doi.org/10.1111/pce.13322, 2018.
Cruiziat, P., Cochard, H., and Améglio, T.: Hydraulic architecture of
trees: main concepts and results, Ann. For. Sci., 59, 723–752,
https://doi.org/10.1051/forest:2002060, 2002.
De Cáceres, M., Martínez-Vilalta, J., Coll, L., Llorens, P.,
Casals, P., Poyatos, R., Pausas, J. G., and Brotons, L.: Coupling a water
balance model with forest inventory data to predict drought stress: The role
of forest structural changes vs. climate changes, Agric. For. Meteorol.,
213, 77–90, https://doi.org/10.1016/j.agrformet.2015.06.012, 2015.
De Cáceres, M., Mencuccini, M., Martin-StPaul, N., Limousin, J. M.,
Coll, L., Poyatos, R., Cabon, A., Granda, V., Forner, A., Valladares, F.,
and Martínez-Vilalta, J.: Unravelling the effect of species mixing on
water use and drought stress in Mediterranean forests: A modelling approach,
Agric. For. Meteorol., 296, 108233, https://doi.org/10.1016/j.agrformet.2020.108233,
2021.
De Kauwe, M. G., Medlyn, B. E., Ukkola, A. M., Mu, M., Sabot, M. E. B.,
Pitman, A. J., Meir, P., Cernusak, L. A., Rifai, S. W., Choat, B., Tissue,
D. T., Blackman, C. J., Li, X., Roderick, M., and Briggs, P. R.: Identifying
areas at risk of drought-induced tree mortality across South-Eastern
Australia, Glob. Change Biol., 26, 5716–5733, https://doi.org/10.1111/gcb.15215,
2020.
Domec, J. C., Smith, D. D., and McCulloh, K. A.: A synthesis of the effects
of atmospheric carbon dioxide enrichment on plant hydraulics: implications
for whole-plant water use efficiency and resistance to drought, Plant Cell
Environ., 40, 921–937, https://doi.org/10.1111/pce.12843, 2017.
Dufour-Kowalski, S., Courbaud, B., Dreyfus, P., Meredieu, C., and De
Coligny, F.: Capsis: An open software framework and community for forest
growth modelling, Ann. Forest Sci., 221–233,
https://doi.org/10.1007/s13595-011-0140-9, 2012.
Dufrêne, E., Davi, H., François, C., Maire, G. le, Dantec, V. L.,
and Granier, A.: Modelling carbon and water cycles in a beech forest: Part
I: Model description and uncertainty analysis on modelled NEE, Ecol. Model.,
185, 407–436, https://doi.org/10.1016/j.ecolmodel.2005.01.004, 2005.
Dutykh, D.: How to overcome the Courant-Friedrichs-Lewy condition of
explicit discretizations?, Numer. Methods Diffus. Phenom. Build. Phys.,
103–120, https://doi.org/10.1007/978-3-030-31574-0_5, 2016.
Duursma, R. A., Blackman, C. J., Lopéz, R., Martin-StPaul, N. K.,
Cochard, H., and Medlyn, B. E.: On the minimum leaf conductance: its role in
models of plant water use, and ecological and environmental controls, New
Phytol., 221, 693–705, https://doi.org/10.1111/nph.15395, 2019.
Fargeon, H., Pimont, F., Martin-StPaul, N., De Caceres, M., Ruffault, J.,
Barbero, R., and Dupuy, J. L.: Projections of fire danger under climate
change over France: where do the greatest uncertainties lie?, Clim. Change,
160, 479–493, https://doi.org/10.1007/s10584-019-02629-w, 2020.
Fatichi, S., Pappas, C., and Ivanov, V. Y.: Modeling plant–water
interactions: an ecohydrological overview from the cell to the global scale,
Wiley Interdiscip. Rev. Water, 3, 327–368,
https://doi.org/10.1002/wat2.1125, 2016.
Feng, X., Ackerly, D. D., Dawson, T. E., Manzoni, S., Skelton, R. P., Vico,
G., and Thompson, S. E.: The ecohydrological context of drought and
classification of plant responses, Ecol. Lett., 21, 1723–1736,
https://doi.org/10.1111/ele.13139, 2018.
Fettig, C. J., Mortenson, L. A., Bulaon, B. M., and Foulk, P. B.: Tree
mortality following drought in the central and southern Sierra Nevada,
California, U.S., For. Ecol. Manag., 432, 164–178,
https://doi.org/10.1016/j.foreco.2018.09.006, 2019.
Granier, A., Bréda, N., Biron, P., and Villette, S.: A lumped water
balance model to evaluate duration and intensity of drought constraints in
forest stands, Ecol. Model., 116, 269–283,
https://doi.org/10.1016/S0304-3800(98)00205-1, 1999.
Guillemot, J., Martin-StPaul, N. K., Bulascoschi, L., Poorter, L., Morin,
X., Pinho, B. X., le Maire, G., R. L. Bittencourt, P., Oliveira, R. S.,
Bongers, F., Brouwer, R., Pereira, L., Gonzalez Melo, G. A., Boonman, C. C.
F., Brown, K. A., Cerabolini, B. E. L., Niinemets, Ü., Onoda, Y.,
Schneider, J. V., Sheremetiev, S., and Brancalion, P. H. S.: Small and slow
is safe: On the drought tolerance of tropical tree species, Glob. Change
Biol., 28, 2622–2638, https://doi.org/10.1111/gcb.16082, 2022.
Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., and Or, D.: SoilKsatDB: global database of soil saturated hydraulic conductivity measurements for geoscience applications, Earth Syst. Sci. Data, 13, 1593–1612, https://doi.org/10.5194/essd-13-1593-2021, 2021.
Hengl, T., Jesus, J. M. de, Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda,
M., Blagotiæ, A., Shangguan, W., Wright, M. N., Geng, X.,
Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A.,
Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and
Kempen, B.: SoilGrids250m: Global gridded soil information based on machine
learning, PLOS ONE, 12, e0169748,
https://doi.org/10.1371/journal.pone.0169748, 2017.
Hoff, C. and Rambal, S.: An examination of the interaction between climate,
soil and leaf area index in a Quercus ilex ecosystem, Ann. For. Sci., 60,
153–161, https://doi.org/10.1051/forest:2003008, 2003.
Hölttä, T., Cochard, H., Nikinmaa, E., and Mencuccini, M.:
Capacitive effect of cavitation in xylem conduits: results from a dynamic
model, Plant Cell Environ., 32, 10–21, 2009.
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E.,
and Schulze, E. D.: A global analysis of root distributions for terrestrial
biomes, Oecologia, 108, 389–411, https://doi.org/10.1007/BF00333714, 1996.
Jactel, H., Petit, J., Desprez-Loustau, M. L., Delzon, S., Piou, D.,
Battisti, A., and Koricheva, J.: Drought effects on damage by forest insects
and pathogens: A meta-analysis, Glob. Change Biol., 18, 267–276,
https://doi.org/10.1111/j.1365-2486.2011.02512.x, 2012.
Jarvis, P. G.: The interpretation of the variations in leaf water potential
and stomatal conductance found in canopies in the field, Philos. T. Roy.
Soc. Lond. B, 273, 593–610,
https://doi.org/10.1098/rstb.1976.0035, 1976.
Jones, H. G.: Plants and microclimate: A quantitative approach to
environmental plant physiology, Cambridge University Press,
https://doi.org/10.1017/CBO9780511845727, 2013.
Kennedy, D., Swenson, S., Oleson, K. W., Lawrence, D. M., Fisher, R., Lola
da Costa, A. C., and Gentine, P.: Implementing Plant Hydraulics in the
Community Land Model, Version 5, J. Adv. Model. Earth Syst., 11, 485–513,
https://doi.org/10.1029/2018MS001500, 2019.
Klein, T.: The variability of stomatal sensitivity to leaf water potential
across tree species indicates a continuum between isohydric and anisohydric
behaviours, Funct. Ecol., 28, 1313–1320,
https://doi.org/10.1111/1365-2435.12289, 2014.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Lemaire, C., Blackman, C. J., Cochard, H., Menezes-Silva, P. E.,
Torres-Ruiz, J. M., and Herbette, S.: Acclimation of hydraulic and
morphological traits to water deficit delays hydraulic failure during
simulated drought in poplar, Tree Physiol., 41, 2008–2021, 2021.
Lens, F., Picon-Cochard, C., Delmas, C. E. L., Signarbieux, C., Buttler, A., Cochard, H., Jansen,
S., Chauvin, T., Doria, L. C., Del Arco, M., and Delzon, S.: Herbaceous angiosperms are not
more vulnerable to drought-induced embolism than angiosperm trees, Plant Physiol., 172,
661–667, https://doi.org/10.1104/PP.16.00829, 2016.
Li, L., Yang, Z., Matheny, A. M., Zheng, H., Swenson, S. C., Lawrence, D.
M., Barlage, M., Yan, B., McDowell, N. G., and Leung, L. R.: Representation
of Plant Hydraulics in the Noah-MP Land Surface Model: Model Development and
Multi-scale Evaluation, J. Adv. Model. Earth Syst., 13, e2020MS002214,
https://doi.org/10.1029/2020ms002214, 2021.
Lin, Y.-S., Medlyn, B. E., Duursma, R. A., Prentice, I. C., Wang, H., Baig,
S., Eamus, D., de Dios, V. R., Mitchell, P., Ellsworth, D. S., de Beeck, M.
O., Wallin, G., Uddling, J., Tarvainen, L., Linderson, M.-L., Cernusak, L.
A., Nippert, J. B., Ocheltree, T. W., Tissue, D. T., Martin-StPaul, N. K.,
Rogers, A., Warren, J. M., De Angelis, P., Hikosaka, K., Han, Q., Onoda, Y.,
Gimeno, T. E., Barton, C. V. M., Bennie, J., Bonal, D., Bosc, A., Löw,
M., Macinins-Ng, C., Rey, A., Rowland, L., Setterfield, S. A., Tausz-Posch,
S., Zaragoza-Castells, J., Broadmeadow, M. S. J., Drake, J. E., Freeman, M.,
Ghannoum, O., Hutley, L. B., Kelly, J. W., Kikuzawa, K., Kolari, P., Koyama,
K., Limousin, J.-M., Meir, P., Lola da Costa, A. C., Mikkelsen, T. N.,
Salinas, N., Sun, W., and Wingate, L.: Optimal stomatal behaviour around the
world, Nat. Clim. Change, 5, 459–464, https://doi.org/10.1038/nclimate2550,
2015.
López, R., Cano, F. J., Martin-StPaul, N. K., Cochard, H., and Choat,
B.: Coordination of stem and leaf traits define different strategies to
regulate water loss and tolerance ranges to aridity, New Phytol., 230,
497–509, 2021.
Mackay, D. S., Ahl, D. E., Ewers, B. E., Samanta, S., Gower, S. T., and
Burrows, S. N.: Physiological tradeoffs in the parameterization of a model
of canopy transpiration, Adv. Water Resour., 26, 179–194,
https://doi.org/10.1016/S0309-1708(02)00090-8, 2003.
Mantova, M., Menezes-Silva, P. E., Badel, E., Cochard, H., and Torres-Ruiz,
J. M.: The interplay of hydraulic failure and cell vitality explains tree
capacity to recover from drought, Physiol. Plant., 172, 13331,
https://doi.org/10.1111/ppl.13331, 2021.
Martinez-Vilalta, J., Anderegg, W. R. L., Sapes, G., and Sala, A.: Greater
focus on water pools may improve our ability to understand and anticipate
drought-induced mortality in plants, New Phytol., 223, 22–32,
https://doi.org/10.1111/nph.15644, 2019.
Martin-StPaul, N., Delzon, S., and Cochard, H.: Plant resistance to drought
depends on timely stomatal closure, Ecol. Lett., 20, 1437–1447,
https://doi.org/10.1111/ele.12851, 2017.
McDowell, N. G., Brodribb, T. J., and Nardini, A.: Hydraulics in the 21st
century, New Phytol., 224, 537–542, https://doi.org/10.1111/nph.16151,
2019.
McDowell, N. G., Sapes, G., Pivovaroff, A., Adams, H. D., Allen, C. D.,
Anderegg, W. R. L., Arend, M., Breshears, D. D., Brodribb, T., Choat, B.,
Cochard, H., De Cáceres, M., De Kauwe, M. G., Grossiord, C., Hammond, W.
M., Hartmann, H., Hoch, G., Kahmen, A., Klein, T., Mackay, D. S., Mantova,
M., Martínez-Vilalta, J., Medlyn, B. E., Mencuccini, M., Nardini, A.,
Oliveira, R. S., Sala, A., Tissue, D. T., Torres-Ruiz, J. M., Trowbridge, A.
M., Trugman, A. T., Wiley, E., and Xu, C.: Mechanisms of woody-plant
mortality under rising drought, CO2 and vapour pressure deficit, Nat. Rev.
Earth Environ., 3, 294–308, https://doi.org/10.1038/s43017-022-00272-1,
2022.
Meinzer, F. C., Woodruff, D. R., Domec, J.-C., Goldstein, G., Campanello, P.
I., Gatti, M. G., and Villalobos-Vega, R.: Coordination of leaf and stem
water transport properties in tropical forest trees, Oecologia, 156, 31–41,
https://doi.org/10.1007/s00442-008-0974-5, 2008.
Meir, P., Meir, P., Mencuccini, M., and Dewar, R. C.: Tansley insight
Drought-related tree mortality: addressing the gaps in understanding and
prediction, New Phytol., 207, 28–33, 2015.
Mencuccini, M., Manzoni, S., and Christoffersen, B.: Modelling water fluxes
in plants: from tissues to biosphere, New Phytol., 222, 1207–1222,
https://doi.org/10.1111/nph.15681, 2019.
Moreaux, V., Martel, S., Bosc, A., Picart, D., Achat, D., Moisy, C., Aussenac, R., Chipeaux, C., Bonnefond, J.-M., Figuères, S., Trichet, P., Vezy, R., Badeau, V., Longdoz, B., Granier, A., Roupsard, O., Nicolas, M., Pilegaard, K., Matteucci, G., Jolivet, C., Black, A. T., Picard, O., and Loustau, D.: Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0, Geosci. Model Dev., 13, 5973–6009, https://doi.org/10.5194/gmd-13-5973-2020, 2020.
Morin, X., Bugmann, H., de Coligny, F., Martin-StPaul, N., Cailleret, M.,
Limousin, J.-M., Ourcival, J.-M., Prevosto, B., Simioni, G., Toigo, M.,
Vennetier, M., Catteau, E., and Guillemot, J.: Beyond forest succession: A
gap model to study ecosystem functioning and tree community composition
under climate change, Funct. Ecol., 35, 955–975,
https://doi.org/10.1111/1365-2435.13760, 2021.
Mouillot, F., Rambal, S., and Lavorel, S.: A generic process-based SImulator
for meditERRanean landscApes (SIERRA): design and validation exercises, For.
Ecol. Manag., 147, 75–97, 2001.
Nolan, R. H., Blackman, C. J., de Dios, V. R., Choat, B., Medlyn, B. E., Li,
X., Bradstock, R. A., and Boer, M. M.: Linking Forest Flammability and Plant
Vulnerability to Drought, Forests, 11, 779,
https://doi.org/10.3390/f11070779, 2020.
Pammenter, N. W. and Vander Willigen, C.: A mathematical and statistical
analysis of the curves illustrating vulnerability of xylem to cavitation,
Tree Physiol., 18, 589–593, 1998.
Pimont, F., Ruffault, J., Martin-StPaul, N. K., and Dupuy, J.-L.: Why is the effect of live fuel
moisture content on fire rate of spread underestimated in field experiments in shrublands?,
Int. J. Wildland Fire, 28, 127–137, https://doi.org/10.1071/WF18091, 2019.
Rambal, S.: The differential role of mechanisms for drought resistance in a
Mediterranean evergreen shrub: a simulation approach, Plant Cell Environ.,
16, 35–44, https://doi.org/10.1111/j.1365-3040.1993.tb00842.x, 1993.
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for
Statistical Computing, Vienna, Austria, 2020.
Riederer, M. and Schreiber, L.: Protecting against water loss: analysis of
the barrier properties of plant cuticles, J. Exp. Bot., 52, 2023–2032,
https://doi.org/10.1093/jexbot/52.363.2023, 2001.
Rowland, L., Martínez-Vilalta, J., and Mencuccini, M.: Hard times for
high expectations from hydraulics: predicting drought-induced forest
mortality at landscape scales remains a challenge, New Phytol., 230,
1685–1687, https://doi.org/10.1111/nph.17317, 2021.
Ruffault, J., Martin-StPaul, N. K. N., Rambal, S., and Mouillot, F.:
Differential regional responses in drought length, intensity and timing to
recent climate changes in a Mediterranean forested ecosystem, Clim. Change,
117, 103–117, https://doi.org/10.1007/s10584-012-0559-5, 2013.
Ruffault, J., Martin-StPaul, N. K., Duffet, C., Goge, F., and Mouillot, F.:
Projecting future drought in Mediterranean forests: Bias correction of
climate models matters!, Theor. Appl. Climatol., 117, 113–122,
https://doi.org/10.1007/s00704-013-0992-z, 2014.
Ruffault, J., Curt, T., Martin-StPaul, N. K., Moron, V., and Trigo, R. M.: Extreme wildfire events are linked to global-change-type droughts in the northern Mediterranean, Nat. Hazards Earth Syst. Sci., 18, 847–856, https://doi.org/10.5194/nhess-18-847-2018, 2018a.
Ruffault, J., Martin-StPaul, N., Pimont, F., and Dupuy, J.-L.: How well do
meteorological drought indices predict live fuel moisture content (LFMC)? An
assessment for wildfire research and operations in Mediterranean ecosystems,
Agric. For. Meteorol., 262, 391–401,
https://doi.org/10.1016/j.agrformet.2018.07.031, 2018b.
Ruffault, J., Curt, T., Moron, V., Trigo, R. M., Mouillot, F., Koutsias, N.,
Pimont, F., Martin-StPaul, N. K., Barbero, R., Dupuy, J. L., Russo, A., and
Belhadj-Kheder, C.: Increased likelihood of heat-induced large wildfires in
the Mediterranean Basin, Sci. Rep.-UK, 10, 13790,
https://doi.org/10.1101/2020.01.09.896878, 2020.
Ruffault, J., Martin-StPaul, N., and Pimont, F.: SurEau-Ecos v2.0.1 (v2.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.5878978, 2022.
Schuldt, B., Buras, A., Arend, M., Vitasse, Y., Beierkuhnlein, C., Damm, A.,
Gharun, M., Grams, T. E. E., Hauck, M., Hajek, P., Hartmann, H.,
Hiltbrunner, E., Hoch, G., Holloway-Phillips, M., Körner, C., Larysch,
E., Lübbe, T., Nelson, D. B., Rammig, A., Rigling, A., Rose, L., Ruehr,
N. K., Schumann, K., Weiser, F., Werner, C., Wohlgemuth, T., Zang, C. S.,
and Kahmen, A.: A first assessment of the impact of the extreme 2018 summer
drought on Central European forests, Basic Appl. Ecol., 45, 86–103,
https://doi.org/10.1016/j.baae.2020.04.003, 2020.
Seidl, R., Schelhaas, M.-J., Rammer, W., and Verkerk, P. J.: Increasing
forest disturbances in Europe and their impact on carbon storage, Nat. Clim.
Change, 4, 806–810, 2014.
Sergent, A. S., Varela, S. A., Barigah, T. S., Badel, E., Cochard, H., Dalla-Salda, G., Delzon, S.,
Fernández, M. E., Guillemot, J., Gyenge, J., Lamarque, L. J., Martinez-Meier, A., Rozenberg,
P., Torres-Ruiz, J. M., and Martin-StPaul, N. K.: A comparison of five methods to assess
embolism resistance in trees, For. Ecol. Manag., 468, 118175,
https://doi.org/10.1016/j.foreco.2020.118175, 2020.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J. O., Levis, S., Lucht, W., and Sykes, M. T.: Evaluation of
ecosystem dynamics, plant geography and terrestrial carbon cycling in the
LPJ dynamic global vegetation model, Glob.
Change Biol., 9, 161–185, 2003.
Sobol, I. M.: Global sensitivity indices for nonlinear mathematical models
and their Monte Carlo estimates, Math. Comput. Simul., 55, 271–280, 2001.
Sperry, J. S., Adler, F. R., Campbell, G. S., and Comstock, J. P.:
Limitation of plant water use by rhizosphere and xylem conductance: results
from a model, Plant Cell Environ., 21, 347–359,
https://doi.org/10.1046/j.1365-3040.1998.00287.x, 1998.
Sperry, J. S., Venturas, M. D., Anderegg, W. R. L., Mencuccini, M., Mackay,
D. S., Wang, Y., and Love, D. M.: Predicting stomatal responses to the
environment from the optimization of photosynthetic gain and hydraulic cost,
Plant Cell Environ., 40, 816–830, 2017.
Sterck, F., Markesteijn, L., Schieving, F., and Poorter, L.: Functional
traits determine trade-offs and niches in a tropical forest community, P.
Natl. Acad. Sci. USA, 108, 20627–20632,
https://doi.org/10.1073/pnas.1106950108, 2011.
Tóth, B., Weynants, M., Pásztor, L., and Hengl, T.: 3D soil hydraulic database of Europe at
250 m resolution, Hydrol. Process., 31, 2662–2666, https://doi.org/10.1002/hyp.11203,
2017.
Trenberth, K. E., Dai, A., Van Der Schrier, G., Jones, P. D., Barichivich,
J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought,
Nat. Clim. Change, 4, 17–22, 2014.
Trugman, A. T., Anderegg, L. D. L., Anderegg, W. R. L., Das, A. J., and
Stephenson, N. L.: Why is Tree Drought Mortality so Hard to Predict?, Trends
Ecol. Evol., 36, 520–532, https://doi.org/10.1016/j.tree.2021.02.001, 2021.
Tuzet, A., Granier, A., Betsch, P., Peiffer, M., and Perrier, A.: Modelling
hydraulic functioning of an adult beech stand under non-limiting soil water
and severe drought condition, Ecol. Model., 348, 56–77,
https://doi.org/10.1016/j.ecolmodel.2017.01.007, 2017.
Tyree, M. T. and Ewers, F. W.: The hydraulic architecture of trees and other
woody plants, New Phytol., 119, 345–360,
https://doi.org/10.1111/j.1469-8137.1991.tb00035.x, 1991.
Tyree, M. T. and Hammel, H. T.: The Measurement of the turgor pressure and
the water relations of plants by the pressure-bomb technique, J. Exp. Bot.,
23, 267–282, https://doi.org/10.1093/jxb/23.1.267, 1972.
Tyree, M. T. and Yang, S.: Water-storage capacity ofThuja, Tsuga andAcer
stems measured by dehydration isotherms, Planta, 182, 420–426, 1990.
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic
conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892,
https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Venturas, M. D., Todd, H. N., Trugman, A. T., and Anderegg, W. R. L.:
Understanding and predicting forest mortality in the western United States
using long-term forest inventory data and modeled hydraulic damage, New
Phytol., 230, 1896–1910, https://doi.org/10.1111/nph.17043, 2020.
Vidal, J. P., Martin, E., Franchistéguy, L., Baillon, M., and
Soubeyroux, J. M.: A 50 year high resolution atmospheric reanalysis over
France with the Safran system, Int. J. Climatol., 30, 1627–1644, 2010.
Wang, Y., Sperry, J. S., Anderegg, W. R. L. L., Venturas, M. D., and
Trugman, A. T.: A theoretical and empirical assessment of stomatal
optimization modeling, New Phytol., 227, 311–325,
https://doi.org/10.1111/nph.16572, 2020.
Williams, M., Rastetter, E. B., Fernandes, D. N., Goulden, M. L., Wofsy, S.
C., Shaver, G. R., Melillo, J. M., Munger, J. W., Fan, S. M., and
Nadelhoffer, K. J.: Modelling the soil-plant-atmosphere continuum in a
Quercus-acer stand at Harvard forest: The regulation of stomatal conductance
by light, nitrogen and soil/plant hydraulic properties, Plant Cell Environ.,
19, 911–927, https://doi.org/10.1111/j.1365-3040.1996.tb00456.x, 1996.
Xu, X., Medvigy, D., Powers, J. S., Becknell, J. M., and Guan, K.: Diversity
in plant hydraulic traits explains seasonal and inter-annual variations of
vegetation dynamics in seasonally dry tropical forests, New Phytol., 212,
80–95, https://doi.org/10.1111/nph.14009, 2016.
Short summary
A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
A widespread increase in tree mortality has been observed around the globe, and this trend is...
